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帕金森病的临床特征:关键症状的演变

Clinical Features of Parkinson's Disease: The Evolution of Critical Symptoms.

作者信息

Váradi Csaba

机构信息

Institute of Chemistry, Faculty of Materials Science and Engineering, University of Miskolc, 3515 Miskolc, Hungary.

出版信息

Biology (Basel). 2020 May 19;9(5):103. doi: 10.3390/biology9050103.

DOI:10.3390/biology9050103
PMID:32438686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7285080/
Abstract

Parkinson's disease (PD) is a multi-attribute neurodegenerative disorder combining motor and nonmotor symptoms without well-defined diagnostic clinical markers. The presence of primary motor features (bradykinesia, rest tremor, rigidity and loss of postural reflexes) are the most characteristic signs of PD that are also utilized to identify patients in current clinical practice. The successful implementation of levodopa treatment revealed that nonmotor features are the main contributors of patient disability in PD, and their occurrence might be earlier than motor symptoms during disease progression. Targeted detection of prodromal PD symptoms can open up new possibilities in the identification of PD patients and provide potential patient populations for developing novel neuroprotective therapies. In this review, the evolution of critical features in PD diagnosis is described with special attention to nonmotor symptoms and their possible detection.

摘要

帕金森病(PD)是一种兼具运动和非运动症状的多属性神经退行性疾病,尚无明确的诊断性临床标志物。原发性运动特征(运动迟缓、静止性震颤、僵硬和姿势反射丧失)的存在是PD最具特征性的体征,目前临床实践中也利用这些体征来识别患者。左旋多巴治疗的成功实施表明,非运动特征是PD患者残疾的主要原因,并且在疾病进展过程中,它们的出现可能早于运动症状。前驱性PD症状的靶向检测可为PD患者的识别开辟新的可能性,并为开发新型神经保护疗法提供潜在的患者群体。在本综述中,描述了PD诊断中关键特征的演变,特别关注非运动症状及其可能的检测方法。

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A mountable toilet system for personalized health monitoring via the analysis of excreta.一种可安装的马桶系统,可通过分析排泄物进行个性化健康监测。
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A systems biology approach towards the identification of candidate therapeutic genes and potential biomarkers for Parkinson's disease.
基因编码的模块化亚细胞器探针揭示了由PRKN基因敲除驱动的溶酶体和线粒体功能障碍。
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Design of a deep fusion model for early Parkinson's disease prediction using handwritten image analysis.基于手写图像分析的早期帕金森病预测深度融合模型设计
Sci Rep. 2025 Jul 1;15(1):20437. doi: 10.1038/s41598-025-04807-6.
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Standardized clinical assessments and advanced AI-driven instruments used to evaluate neurofunctional deficits, including within biomarker based framework, in Parkinson's disease - human intelligence made vs. AI models - systematic review.用于评估帕金森病神经功能缺损的标准化临床评估和先进的人工智能驱动工具,包括在基于生物标志物的框架内——人类智能与人工智能模型的比较——系统评价
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